The Decision Maker

In an industry where data is the most valuable asset, data integrity is essential. Building a successful credit union begins with data integrity.

Credit union data is more abundant than ever. Along with this abundance comes an increased need for data integrity. Databases are constantly being designed with ever-expanding datasets; the integrity of data must be upheld for wise, data-driven decision making. As new applications are being dreamed up by developers within the financial services arena, credit unions are struggling to manage their data that flows throughout their organization. Mobile banking has become one of the biggest disrupting forces by pumping new data types at an alarming rate. If this new data is compromised, all the analytics tools and technologies in the world will not be effective.

3 Types of Data Integrity

Physical Integrity

Data must be physically safe. Whether data is stored internally (on various servers) or within the cloud, credit unions must firmly establish physical data integrity standards. Disaster recovery, security, server maintenance and other actions must be taken to ensure the physical integrity of data.

Human Error

Humans make mistakes. Maintaining data integrity is very difficult when humans are inputting free-form text into software systems throughout the credit union. The design of credit union software must be improved to mitigate human error. Drop-down fields, required formats for data input and auto-populated fields are some of the ways credit unions can decrease the volume of erroneous data caused by humans.

Referential Integrity

Data integrity depends on more than physical and human factors. Every data field must coexist within a credit union’s systems. For example, two databases that contain a member’s e-mail address should not have different values. If the online banking database and the loan origination database have different values for a member’s e-mail address, logic must be built into the credit union’s systems to determine which data element is correct or primary.

Consequences of Lost Integrity

When there is a lack of data integrity, the damages incurred can be tremendous. Thousands of decisions are made at credit unions every day. From marketing campaigns to new loan products, high stakes decisions are made based on the data employees analyze from source systems. When this data loses integrity, many side effects will be felt. Compromised data integrity results in consequences that range from member information being sent with errors to implementing a loan product that results in million dollar losses.

Data Warehousing

The best way to ensure data integrity throughout a credit union is through a data warehouse. Data warehouses are carefully designed (with input from all departments) to ensure data integrity throughout the credit union. Source system databases are designed with a specific function in mind. Credit card, loan origination, and online banking databases are all designed with a specific focus and each vendor designs their databases without thinking how it will be integrated to another vendor’s database.

Integrity of Integration

The word integrity means wholeness and completeness. With the abundance of source systems at an average credit union, data integrity will be impossible without a Single Version Of Truth (SVOT) established in a data warehouse. A unified data model will ensure data is accurate and consistent. As credit unions begin utilizing their data warehouse, they will be able to leverage data that has been integrated from many different sources.

The Power of Integrity

Having accurate and trustworthy data throughout your credit union is crucial. Relying on one SVOT and making decisions from this will bring consistency to all decision-making. A data warehouse that is well managed will ensure that data populated throughout the credit union has been tested for data integrity. Without clean, integrated data, even the most expensive analytics tools (i.e. SAS) will fail to provide value to credit unions.

Credit Unions’ Time to Shine

As competition continues to increase between financial services providers, the brand of each credit union will remain their competitive advantage. Members trust their credit unions, but how long will that trust last? The time is now for credit unions to get their data together, establish data integrity and utilize the powerful analytics tools that are now available to them. Now is the time for Big Data and Analytics in the credit union industry!